On my commute home from Language Log Plaza West yesterday, I heard this brief piece on NPR about Lydia Callis, NYC Mayor Bloomberg's American Sign Language interpreter. (See also here, here, here, here, here — screw it, just search for "Lydia Callis".) A couple choice quotes from some of these stories:

From the NPR piece I heard: Callis was animated – both in her facial expressions and hand movements – the antithesis of the stoic mayor.

From this Bloomberg News piece: "She's awesome," Lynn Correa, 30, who has watched YouTube videos made about Callis, said today at a bus stop in Brooklyn's Williamsburg neighborhood. "She's much more expressive than [Mayor Bloomberg] is."

Don't get me wrong: I think it's great that Callis, and sign language interpreting generally, are getting some postive attention. But looking at the videos, I don't see anything other than a (very good) ASL interpreter — in other words, Callis is not doing anything extra special here, she's just doing her job, which is to translate what people are saying into ASL. I understand that there's the contrast with the otherwise somber Bloomberg, and that what is being translated is news about Hurricane Sandy, and that for many folks this may be one of the first times they've seen sign language interpretation up close — but I can't help pointing out here that the hand movements and facial expressions are defining features of ASL (and of other signed languages). The perception that we non-signers have that these hand movements and facial expressions are particularly "animated" and "expressive" is precisely due to our lack of experience with them as linguistic features.

Over the last couple of weeks, and as a bit of a distraction from finishing off my PhD, I've been working with James Cheshire looking at the use of different languages within my aforementioned dataset of London tweets.

I've been handling the data generation side, and the method really is quite simple. Just like some similar work carried out by Eric Fischer, I've employed the Chromium Compact Language Detector – a open-source Python library adapted from the Google Chrome algorithm to detect a website's language – in detecting the predominant language contained within around 3.3 million geolocated tweets, captured in London over the course of this summer. […]

One issue with this approach that I did note was the surprising popularity of Tagalog, a language of the Philippines, which initially was identified as the 7th most tweeted language. On further investigation, I found that many of these classifications included just uses of English terms such as 'hahahahaha', 'ahhhhhhh' and 'lololololol'. I don't know much about Tagalog but it sounds like a fun language. Nevertheless, Tagalog was excluded from our analysis.

Yesterday, I sent this message to the newsroom staff: We will not be using the word “Frankenstorm” in coverage of Hurricane Sandy, because the term trivializes a serious and potentially deadly event. It’s acceptable in direct quotes, but even there we shouldn’t overdo it.

Mitt Romney sometimes exhibits a rapid repetition of phrase-initial function words, often intermixed with um and uh. This behavior was especially frequent in the third presidential debate (10/22/2012). Here's an example from the beginning of his first response:

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um uh this is obviously an area of great concern to the entire world
and to America in particular,
which is to see
uh a- a complete change in the- the- the- the structure and the- um the environment in the Middle East.

Just the last phrase:

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uh a- a complete change in the- the- the- the structure and the- um the environment in the Middle East.

Somehow, Language Log has yet to take notice of the international sensation that is "Gangnam Style," the deliciously weird Korean pop video that currently has more than 560 million views on YouTube. Here's a good opportunity to rectify that oversight: among the countless spoofs of the video is this one by enterprising MIT students, featuring a cameo by Noam Chomsky at 3:20.

English is a little bit like a child. We love and nurture it into being, and once it gains gross motor skills, it starts going exactly where we don’t want it to go: it heads right for the goddamned light sockets. We put it in nice clothes and tell it to make friends, and it comes home covered in mud, with its underwear on its head and someone else’s socks on its feet. We ask it to clean up or to take out the garbage, and instead it hollers at us that we don’t run its life, man. Then it stomps off to its room to listen to The Smiths in the dark.

Everything we’ve done to and for English is for its own good, we tell it (angrily, as it slouches in its chair and writes “irregardless” all over itself in ballpoint pen). This is to help you grow into a language people will respect! Are you listening to me? Why aren’t you listening to me??

Like well-adjusted children eventually do, English lives its own life. We can tell it to clean itself up and act more like one of the Classical languages (I bet Latin doesn’t sneak German in through its bedroom window, does it?). We can threaten, cajole, wheedle, beg, yell, throw tantrums, and start learning French instead. But no matter what we do, we will never really be the boss of it. And that, frankly, is what makes it so beautiful.

Recently announced, a 2013 Benjamin Franklin Medal for William Labov of the University of Pennsylvania. The citation:

For establishing the cognitive basis of language variation and change through rigorous analysis of linguistic data, and for the study of non-standard dialects with significant social and cultural implications.